People diagnosed with a disorder of consciousness (DoC)—a spectrum of consciousness including comatose state—typically have a negative prognosis and their treatment options are limited. We interviewed seven clinical care providers who are involved in caring for DoC patients to explore the potential for technology to facilitate treatment and care of DoC patients. The interviews revealed multiple rich opportunities in this space centered around optimizing sensory stimulation—the systematic delivery of sights, sounds, smells, tastes, and touch. Simultaneously, the interviews also revealed many ethical and technical challenges inherent in DoC patient care, including difficulty in obtaining familiar media to use in the delivery of the sensory stimulation. Our findings underscore the need for technology that complements, not replaces, the human elements of DoC care and healthcare more generally.

Financial institutions are required by their governments to detect and deter criminal activity, commonly known as Anti-Money Laundering (AML). AML professionals use a constellation of software tools to facilitate this work; The design of these tools and the way they fit together can impact the effectiveness of an investigation and the amount of effort required. We conducted 15 semi-structured interviews of AML professionals and analyzed their responses using reflexive thematic analysis. The results reveal a breadth of socio-technical challenges that financial institutions face in implementing an AML system. Many AML systems fail to address all aspects of an institution’s workflow and lack necessary data leading users to follow manual processes and workarounds. These shortcomings provide opportunity for the use of ML/AI— based technologies. These results inform design considerations for AML systems, and add financial institutions to the empirical literature around designing and deploying collaborative systems for enterprise settings.

The upsurge in remote and hybrid work practices has prompted researchers to explore the technological, organizational, and psychological dimensions of remote work. However, the nuanced dynamics of balancing familial duties, especially care work for older adults, and professional work is often overlooked in the literature. This balancing act introduces unique stressors, blurring work and personal life boundaries, potentially causing physical stress or prompting care providers to leave their jobs. The inherent nature of remote work executed within the familial sphere underscores the importance of understanding how care responsibilities impact the remote work experience. This study addresses this gap by focusing on informal care providers, an understudied population in the CSCW remote work literature. Through a diary study and interviews, we investigate challenges remote workers face and the role of technology in their work. Findings highlight the prevalence of care work, emphasizing the need for targeted technological interventions to support the well-being and productivity of remote workers managing care duties. Critical challenges include familial responsibilities on higher-stress days, lack of communication regarding availability, personal time sacrifices for productivity, coordination in place making among care providers, and multitasking on days with familial responsibilities or distractions. This exploratory study underscores the importance of assisting care providers in a way that embraces their (possible) role as remote workers, offering insights for future research and technological interventions to support remote workers navigating the complexities of care work.

Design empathy is a core HCI concept for understanding user perspectives in design processes. Although researchers advocate for leveraging design empathy in the design of assistive technology, educating novice designers about this is challenging; this is especially true in HCI classrooms when the target population includes people with disabilities, and students who do not have a disability are less aware of the diversity of disability. To help students better understand disability experiences, HCI education often adopts “be-like” (mimicking disabled-experience) approaches. However, accessibility researchers advocate adopting the “be-with” approach—learning about other’s experiences through companionship. To mitigate the logistical challenges of being-with in a classroom setting, we developed a “be-connected” approach, which facilitates learning about the disability experience through the narratives of real individuals. Using social media posts from a spinal cord injury subreddit, we developed and deployed an activity aiming to develop design empathy. Our qualitative evaluation showed a notable transformation in students’ design thinking process, suggesting an opportunity to leverage social media data to learn about disabled perspectives and develop design empathy.

Individuals who have sustained a Spinal Cord Injury (SCI) undergo abrupt changes in their functional abilities, impacting all aspects of their lives and imposing a life-long reliance on assistive tools and support from others. This paper aims to understand individuals’ support-seeking behavior in social media as they adjust to their “new normal”—life with reduced mobility and sensation. To understand their online support-seeking behavior, we conducted content analysis on 960 post-threads from SCI-specific subreddit groups. We found that individuals seek informational and emotional support regardless of injury level and time elapsed since injury. Additionally, individuals seek and receive online informational support concerning assistive logistics, motor-functionality, newly acquired self-care, and daily living activities. Similarly, individuals seek emotional support for motivation, and creating new self-identity. Finally, we discuss how social media support dynamics might facilitate reconstructing self-identity, adopting assistive technology, and improving relationships to help adjust to the “new normal.”

Smart hospital patient rooms integrate smart devices for digital control of both entertainment (e.g., television and sound system) and the environment (e.g., lights, blinds, and temperature). While primarily designed to enhance the patient experience, this technology also impacts the hospital employees who work in these patient rooms. This study explores hospital employee experiences with smart patient rooms. We conducted 23 interviews with rehabilitation healthcare professionals, including nurses, doctors, psychologists, and occupational, physical, and speech therapists, to understand their perspectives on working in smart patient rooms. Drawn from thematic analysis of the interviews, our findings offer insights into employees’ current use of the technology, the benefits and drawbacks they encounter, and their suggestions for improving the technology. These findings shed light on the complex problem of building smart patient rooms that simultaneously support the needs of multiple stakeholders, including patients and employees; they also point to important considerations for future designs.

The future of accessibility research is a topic we take up every day as researchers; yet it is important also to step back and ask ourselves about the most important, and overlooked, areas for inquiry in our field. With the rapid pace of change in both computational capabilities and the environmental, social, and political context in which disability plays out, we believe this is a critical time for such inquiry. This is even more important given the relatively narrow set of topics that accessibility research has focused on for most of our field’s history. We invite our community to come together to define what the next generation of accessibility research should engage with.

Smart patient rooms are arriving; however, their value has yet to be explored. We interviewed 20 patients in a rehabilitation hospital, which has patient rooms equipped with off-the-shelf smart home technologies, so the entertainment and environment are digitally controllable. This novel implementation supports varying control abilities through touchscreen, voice command, and accessibility controllers. The smart rooms and controls are potentially transformative for patients with reduced motor function, helping them regain lost independence and control of their surroundings. Through semi-structured interviews, we explore how smart home technology deployed in patient rooms: interacts with patients’ needs, presents new challenges, and fits into the hospital context. We identify a range of considerations that inform how hospitals can integrate smart technology into their environment, including technology design considerations and adjustments to how hospital staff supports its use. These results take an important step toward understanding and improving the value of smart patient rooms.

Many tools are designed to support users in maintaining or developing strong time management practices. Abandonment of these specialized tools is common, in favor of returning to a more general-purpose unstructured tool. How can designs leverage the familiarity of general-purpose tools and the advantages of specialized ones? We explore if applying a time-management-specific understanding of conventions and interactions within unstructured plaintext can be a successful approach to designing support for these tasks. We report the results of two field deployments (combined n=29) of “Plan” - a mobile application with a notes-application-based interface designed to support the practice of Time Management Planning. We show that modest, domain-specific modifications of general-purpose designs can facilitate users’ pre-existing workflows and nudge them towards better practices while leaving interfaces familiar and flexible. However, those with minimal planning experience desired additional structure.

User research for scientific software can inform design and account for the unique concerns of academic researchers. In this study, we explored the user experience on a testbed for cloud computing research, CloudLab. Through 15 semi-structured interviews and observation, we observed the importance of time as a resource to system users. We observed CloudLab users strategically coordinating their time on the platform with other users, navigating the constraints of publication and other academic deadlines. Surprisingly, we found that this coordination may involve altruistic behaviors where users share time on CloudLab that had been allocated for personal use. In light of prior CSCW literature on how actors seek to harness time, we propose concrete opportunities for design interventions. Our strategy across all possible interventions is to increase users' awareness of the rhythms affecting their peers' platform use, allowing coordination based not just on knowledge of CloudLab reservations but also users' progress toward deadlines. The implications of this work inform the design of other similar cyberinfrastructure systems in science where users independently coordinate use of resources.

The balance between protecting user privacy while providing cost-effective devices that are functional and usable is a key challenge in the burgeoning Internet of Things (IoT). In traditional desktop and mobile contexts, the primary user interface is a screen; however, in IoT devices, screens are rare or very small, invalidating many existing approaches to protecting user privacy. Privacy visualizations are a common approach for assisting users in understanding the privacy implications of web and mobile services. To gain a thorough understanding of IoT privacy, we examine existing web, mobile, and IoT visualization approaches. Following that, we define five major privacy factors in the IoT context: type, usage, storage, retention period, and access. We then describe notification methods used in various contexts as reported in the literature. We aim to highlight key approaches that developers and researchers can use for creating effective IoT privacy notices that improve user privacy management (awareness and control). Using a toolkit, a use case scenario, and two examples from the literature, we demonstrate how privacy visualization approaches can be supported in practice.

The COVID-19 pandemic forced researchers to find new ways to continue research, as universities and laboratories experienced closure due to nationwide lockdowns in many countries worldwide, including conducting experiments, workshops, and ethnographic work online. While this had a significant impact on the majority of research work across SIGCHI, research relating to disability and ageing was most impacted due to the additional challenges of recruiting participants, finding accessible online platforms, and ensuring seamless participation while juggling platform accessibility issues, facilitation, and supporting participants’ needs. These challenges were more extreme for disabled researchers. In this workshop, we aim to bring together researchers, designers, and practitioners to explore effective strategies and brainstorm actionable guidelines for supporting disability inclusive online research methods and platforms.

Individuals with spinal cord injury (SCI) need to perform numerous self-care behaviors, some very frequently. Pressure reliefs (PRs), which prevent life-threatening pressure ulcers (PUs), are one such behavior. We conducted a qualitative study with seven individuals with severe SCI—who depend on power wheelchairs—to explore their current PR behavior and the potential for technology to facilitate PR adherence. While our participants were highly motivated to perform PRs because of prior PUs, we found that their understanding of how and when to perform a PR differed by individual, and that while they sometimes forgot to perform PR, in other cases contextual factors made it difficult to perform a PR. Our findings provide insight into the complexity of this design space, identify design considerations for designing technology to facilitate these behaviors, and demonstrate the opportunity for personal informatics to be more inclusive by supporting the needs of this population.

Personal informatics research helps people track personal data for the purposes of self-reflection and gaining self-knowledge. This field, however, has predominantly focused on the data collection and insight-generation elements of self-tracking, with less attention paid to flexible data analysis. As a result, this inattention has led to inflexible analytic pipelines that do not reflect or support the diverse ways people want to engage with their data. This paper contributes a review of personal informatics and visualization research literature to expose a gap in our knowledge for designing flexible tools that assist people engaging with and analyzing personal data in personal contexts, what we call the personal informatics analysis gap. We explore this gap through a multistage longitudinal study on how asthmatics engage with personal air quality data, and we report how participants: were motivated by broad and diverse goals; exhibited patterns in the way they explored their data; engaged with their data in playful ways; discovered new insights through serendipitous exploration; and were reluctant to use analysis tools on their own. These results present new opportunities for visual analysis research and suggest the need for fundamental shifts in how and what we design when supporting personal data analysis.

Individuals with spinal cord injuries (SCI) can have multiple cognitive and physical disabilities because of their injury. Appropriately-designed technology can be empowering and transformative for this population. Unfortunately, just like most technologies, user-centered research methods do not directly account for differing motor and communication abilities. This paper synthesizes SCI literature and leverages our own experiences in three research projects spanning five years with SCI users to highlight significant challenges that HCI researchers might face while employing user-centered methods with this population; communication disabilities, motor disabilities, and difficult contextual or environmental factors can make it difficult or impossible to use standard HCI methods when working with SCI users. We conclude with a set of guidelines and challenges for the HCI community to consider, which can be used both when evaluating papers that work with this population, and to fuel development of new methods or approaches that better-serve them.

Time management planning (TMP) is a practice where people plan what they intend to accomplish and when in a given day. The literature indicates behaviors associated with TMP, but not how people specifically engage in them or how technology is involved. We examined TMP practices of 19 graduate students, noting their methods and how they engage with tools. Students utilized different combinations of TMP behaviors, both in comparison to each other and within their own experiences. We then asked them to plan following specific guidelines over five days. Participants implemented these guidelines in unique ways using unstructured tools (paper, notes applications). Together, these findings suggest that to be useful, TMP software must not impose a specific structure. We demonstrate opportunities to incorporate these findings through the design of a flexible mobile application based on notes applications to facilitate planning while encouraging, but not requiring, the use of TMP behaviors.

Sailing has a range of positive impacts on mental and physical health-related quality of life for individuals with tetraplegia. This work describes the iterative design process of creating an adaptive sailing experience that requires minimal training and preparation for individuals with tetraplegia. The Tetra-Sail is an adaptive sailing experience that uses a Shared-Control approach to accept input from both the main user and an experienced adaptive instructor (control partner). This approach was used to create a usable experience for individuals with all types of physical abilities, including participants with high-level and complete spinal cord injuries characterized by loss of sensation and function below their site of injury, with minimal preliminary training. A study of nine participants (five first-time users of Tetra-Sail and four who had used previous iterations) suggested that participants found Tetra-Sail usable and enjoyable. Participants expressed feelings of empowerment, which they attributed to the flexible adaptation to their abilities supported by the implementation of Shared-Control.

Effective design is essential to creating adaptive outdoor activities. Ability-Based Design (ABD) is an approach to accessible design in the HCI literature that we found to be most appealing for this endeavour. ABD focuses on making systems adaptable to users' needs and abilities rather than making the user con-form to system requirements. We explore the principles of ABD in the context of two adaptive outdoor experiences: Tetra-Ski and Tetra-Sail. We found that while the general approach of ABD is useful in this context, some of the basic tenants of ABD can be confounded by: (1) activity risk, (2) dynamic sport environments, and (3) the role of psychological flow during the activity. To accommodate these restrictions on ABD principles and provide a usable experience we developedShared-Control as a collaborative approach to implementation. This paper explores using Shared-Control and ABD principles in the context of these two adaptive recreation systems for individuals with acquired tetraplegia. This perspective reveals tensions between ABD guidelines and designing for adaptive outdoor activities. We reflect on these tensions, potential additions to ABD, and our own usage of Shared-Control as a mechanism for adhering to ABD principles in this context.

Outdoor recreation improves quality of life for individuals with tetraplegia, however providing safe opportunities to engage in these sports has many challenges. We describe the iterative design and field evaluation of Tetra-Ski, a novel power-assisted ski chair. Users control Tetra-Ski with a joystick or Sip-and-Puff controller either independently or collaboratively with a tethered skier through our novel shared-control scheme. We also developed a training simulator to help prepare users prior to their skiing experience. A field study with eight participants and interviews with three trainers who used Tetra-Ski showed that Tetra-Ski is usable, enjoyable, and that the experience has a positive psychosocial effect on users. Furthermore, the shared-control scheme developed for Tetra-Ski proved crucial for supporting the unique abilities of different users, suggesting that a shared-control approach could enable broader access to less-dependent forms of outdoor recreation in the future.

It is increasingly possible to use cameras and sensors to detect and analyze human appearance for the purposes of personalizing user experiences. Such systems are already deployed in some public places to personalize advertisements and recommend items. However, since these technologies are not yet widespread, we do not have a good sense of users' perceptions of the benefits and drawbacks of public display systems that use face detection as an input for personalized recommendations. We conducted a user study with a system that inferred participants' gender and age from a facial detection and analysis algorithm and used this to present recommendations in two scenarios (finding stores to visit in a mall and finding a pair of sunglasses to buy). This work provides an initial step towards understanding user reactions to a new and emerging form of implicit recommendation based on physical appearance.

Everyday, people generate lots of personal data. Driven by the increasing use of online services and widespread adoption of smartphones (owned by 68% of U.S. residents; Anderson, 2015), personal data take many forms, including communications (e.g., e-mail, SMS, Facebook), plans and coordination (e.g., calendars, TripIt, to-do lists), entertainment consumption (e.g., YouTube, Spotify, Netflix), finances (e.g., banking, Amazon, eBay), activities (e.g., steps, runs, check-ins), and even health care (e.g., doctor visits, medications, heart rate). Collectively, these data provide a highly detailed description of an individual. Personal data afford the opportunity for many new kinds of applications that might improve people’s lives through deep personalization, tools to manage personal well-being, and services that support identity construction. However, developers currently encounter challenges working with personal data due to its fragmentation across services. This article evaluates the landscape of personal data, including the systemic forces that created current fragmented collections of data and the process required for integrating data from across services into an application. It details challenges the fragmented ecosystem imposes. Finally, it contributes Phenom, an experimental system that addresses these challenges, making it easier to develop applications that access personal data and providing users with greater control over how their data are used.

People accumulate huge assortments of virtual possessions, but it is not yet clear how systems and system designers can help people make meaning from these large archives. Early research in HCI has suggested that people generally appear to value their virtual things less than their material things, but theory on material possessions does not entirely explain this difference. To investigate if changes to the form and behavior of virtual things may surface valued elements of a virtual archive, we designed a technology probe that selected snippets from old emails and mailed them as physical postcards to participating households. The probe uncovered features of emails that trigger meaningful reflection, and how contextual information can help people engage in reminiscence. Our study revealed insights about how materializing virtual possessions influences factors shaping how people draw on, understand, and value those possessions. We conclude with implication and strategies for aimed at supporting people in having more meaningful interactions and experiences with their virtual possessions.

Effective use of personal data is a core utility of modern smartphones. On Android, several challenges make developing compelling personal data applications difficult. First, personal data is stored in isolated silos. Thus, relationships between data from different providers are missing, data must be queried by source of origin rather than meaning and the persistence of different types of data differ greatly. Second, interfaces to these data are inconsistent and complex. In turn, developers are forced to interleave SQL with Java boilerplate, resulting in error-prone code that does not generalize. Our solution is Epistenet: a toolkit that (1) unifies the storage and treatment of mobile personal data; (2) preserves relationships between disparate data; (3) allows for expressive queries based on the meaning of data rather than its source of origin (e.g., one can query for all communications with John while at the park); and, (4) provides a simple, native query interface to facilitate development.

The promise of "smart" homes, workplaces, schools, and other environments has long been championed. Unattractive, however, has been the cost to run wires and install sensors. More critically, raw sensor data tends not to align with the types of questions humans wish to ask, e.g., do I need to restock my pantry? Although techniques like computer vision can answer some of these questions, it requires significant effort to build and train appropriate classifiers. Even then, these systems are often brittle, with limited ability to handle new or unexpected situations, including being repositioned and environmental changes (e.g., lighting, furniture, seasons). We propose Zensors, a new sensing approach that fuses real-time human intelligence from online crowd workers with automatic approaches to provide robust, adaptive, and readily deployable intelligent sensors. With Zensors, users can go from question to live sensor feed in less than 60 seconds. Through our API, Zensors can enable a variety of rich end-user applications and moves us closer to the vision of responsive, intelligent environments.

How effective are call and SMS logs in modeling tie strength? Frequency and duration of communication has long been cited as a major aspect of tie strength. Intuitively, this makes sense: people communicate with those that they feel close to. Highly cited research papers have pushed this idea further, using communication as a direct proxy for tie strength. However, this operationalization has not been validated. Our work evaluates this assumption. We collected call and SMS logs and ground truth relationship data from 36 participants. Consistent with theory, we found that frequent or long-duration communication likely indicates a strong tie. However, the use of call and SMS logs produced many errors in separating strong and weak ties, suggesting this approach is incomplete. Follow-up interviews indicate fundamental challenges for inferring tie strength from communication logs.

The rapid adoption of smartphones along with a growing habit for using these devices as alarm clocks presents an opportunity to use this device as a sleep detector. This adds value to UbiComp and personal informatics in terms of user context and new performance data to collect and visualize, and it benefits healthcare as sleep is correlated with many health issues. To assess this opportunity, we collected one month of phone sensor and sleep diary entries from 27 people who have a variety of sleep contexts. We used this data to construct models that detect sleep and wake states, daily sleep quality, and global sleep quality. Our system classifies sleep state with 93.06% accuracy, daily sleep quality with 83.97% accuracy, and overall sleep quality with 81.48% accuracy. Individual models performed better than generally trained models, where the individual models require 3 days of ground truth data and 3 weeks of ground truth data to perform well on detecting sleep and sleep quality, respectively. Finally, the features of noise and movement were useful to infer sleep quality.

The smartphone contact list has the potential to be a valuable source of data about personal relationships. To understand how we might data mine the information that people store in their contact lists, we collected the contact lists of 54 participants. Initially we found that the majority of contact list features were unused. However, a further examination of the "name" field revealed a broad variety of contact-naming behaviors. We observed contact "name" fields that included affiliations, relationship role labels, multiple names, phone types, and references to companies/services/places. People's appropriation and usage of contact lists have implications for automated attempts to merge or mine contact lists that assume people use the features and structure of the contact list tool as intended. They also offer new opportunities for data mining to better describe relationships between users and their contacts.

The proliferation of touchscreen devices has made soft keyboards a routine part of life. However, ultra-small computing platforms like the Sony SmartWatch and Apple iPod Nano lack a means of text entry. This limits their potential, despite the fact they are quite capable computers. In this work, we present a soft keyboard interaction technique called ZoomBoard that enables text entry on ultra-small devices. Our approach uses iterative zooming to enlarge otherwise impossibly tiny keys to comfortable size. We based our design on a QWERTY layout, so that it is immediately familiar to users and leverages existing skill. As the ultimate test, we ran a text entry experiment on a keyboard measuring just 16 x 6mm - smaller than a US penny. After eight practice trials, users achieved an average of 9.3 words per minute, with accuracy comparable to a full-sized physical keyboard. This compares favorably to existing mobile text input methods.

Enabling phones to infer whether they are currently in a pocket, purse or on a table facilitates a range of new interactions from placement-dependent notifications setting to preventing "pocket dialing". We collected data from 693 participants to understand where people keep their phone in different contexts and why. Using this data, we identified three placement personas: Single Place Pat, Consistent Casey, and All-over Alex. Based on these results, we collected two weeks of labeled accelerometer data in-situ from 32 participants. We used this data to build models for inferring phone placement, achieving an accuracy of approximately 85% for inferring whether the phone is in an enclosed location and for inferring if the phone is on the user. Finally, we prototyped a capacitive grid and a multispectral sensor and collected data from 15 participants in a laboratory to understand the added value of these sensors.

People engage with many overlapping social networks and enact diverse social roles across different facets of their lives. Unfortunately, many online social networking services reduce most people's contacts to "friend". A richer computational model of relationships would be useful for a number of applications such as managing privacy settings and organizing communications. In this paper, we take a step towards a richer computational model by using call and text message logs from mobile phones to classifying contacts according to life facet (family, work, and social). We extract various features such as communication intensity, regularity, medium, and temporal tendency, and classify the relationships using machine-learning techniques. Our experimental results on 40 users showed that we could classify life facets with up to 90.5% accuracy. The most relevant features include call duration, channel selection, and time of day for the communication.

Social networking site users must decide what content to share and with whom. Many social networks, including Facebook, provide tools that allow users to selectively share content or block people from viewing content. However, sometimes instead of targeting a particular audience, users will self-censor, or choose not to share. We report the results from an 18-participant user study designed to explore self-censorship behavior as well as the subset of unshared content participants would have potentially shared if they could have specifically targeted desired audiences. We asked participants to report all content they thought about sharing but decided not to share on Facebook and interviewed participants about why they made sharing decisions and with whom they would have liked to have shared or not shared. Participants reported that they would have shared approximately half the unshared content if they had been able to exactly target their desired audiences.

There have been many location sharing systems developed over the past two decades, and only recently have they started to be adopted by consumers. In this paper, we present the results of three studies focusing on the foursquare check-in system. We conducted interviews and two surveys to understand, both qualitatively and quantitatively, how and why people use location sharing applications, as well as how they manage their privacy. We also document surprising uses of foursquare, and discuss implications for design of mobile social services.

As ubiquitous computing becomes increasingly mobile and social, personal information sharing will likely increase in frequency, the variety of friends to share with, and range of information that can be shared. Past work has identified that whom you share with is important for choosing whether or not to share, but little work has explored which features of interpersonal relationships influence sharing. We present the results of a study of 42 participants, who self-report aspects of their relationships with 70 of their friends, including frequency of collocation and communication, closeness, and social group. Participants rated their willingness to share in 21 different scenarios based on information a UbiComp system could provide. Our findings show that (a) self-reported closeness is the strongest indicator of willingness to share, (b) individuals are more likely to share in scenarios with common information (e.g. we are within one mile of each other) than other kinds of scenarios (e.g. my location wherever I am), and (c) frequency of communication predicts both closeness and willingness to share better than frequency of collocation.

Modern office work practices increasingly breach traditional boundaries of time and place, increasing breakdowns workers encounter when coordinating interactions with colleagues. We conducted interviews with 12 workers and identified key problems introduced by these practices. To address these problems we developed myUnity, a fully functional platform enabling rich workplace awareness and coordination. myUnity is one of the first integrated platforms to span mobile and desktop environments, both in terms of access and sensing. It uses multiple sources to report user location, availability, tasks, and communication channels. A pilot field study of myUnity demonstrated the significant value of pervasive access to workplace awareness and communication facilities, as well as positive behavioral change in day-to-day communication practices for most users. We present resulting insights about the utility of awareness technology in flexible work environments.